How our implementation at Versuni succeeds through bringing business value to the enterprise by challenging business requirements

The Versuni Landscape consists of mainly SAP systems aligned with SAP's best of suite approach, as shown in the picture below, most SAP solutions, such as SAP Integrated Business Planning (IBP), SAP ARIBA, SAP Data Warehouse Cloud (DWC, now: SAP Datasphere) and SAP Data Intelligence (DI) were relatively new solutions to both us and the rest of the world. Not only did we have to start integrating source systems like IBP and ARIBA into SAP Datasphere using SAP DI without any best practices to fall back on, we also had to ingest external transactional and master data from a diversity of sources, for instance Point-Of-Sales data or production data from OEM factories. This required the setup of various integration channels such as API, e-mail, and FTP. Once the data was available in SAP Datasphere, and the data modeling process was underway, new challenges arose regarding the limitations of a tool you face by being an early adopter. Let us take a deep dive into some of the biggest challenges we had to tackle.

As mentioned before, integrating IBP data was no easy task. IBP is cloud-based and allows for effective supply chain planning. Unfortunately, we were not able to set up a straightforward integration between IBP and SAP Datasphere, as a direct integration option was not available on the Business Technology Platform (BTP). IBP contains a huge amount of data, so together with SAP Product Management, we searched for a solution and got approval on using Cloud Integration/Data Services as an integration tool. This allowed us to make IBP demand and supply planning data available in SAP Datasphere.

Related to this was the integration of SAP ARIBA. ARIBA is an SAP Tool that facilitates the business process of procurement. Currently, we are still working on setting up a secured way of integrating several ARIBA APIs to get the following data into Datasphere.

In the area of supply chain, information is scattered across many different non-SAP systems. Data had to come from several transport partners, warehousing partners, and the terminal operator. Next to that, every party shares data in its own manner. One partner used ANSI coded files pushed via an API, while the other used excel files shared via e-mail. The current set-up of SAP DI allowed us to create data loads to automatically load the data from the various sources into SAP Datasphere. Being able to do so resulted in a data model that incorporated every aspect of the supply chain, allowing the users to efficiently monitor the goods flow.

Also, the lessons we learned from the above-mentioned examples contributed to the current set-up of SAP DI, making it more sustainable and flexible. SAP DI is currently used for ingesting data from a wide range of sources. File integration being the biggest, with a peak number of processed files in 2023 of 93000 a month. Additionally, API, e-mail and other sources are ingested, transformed, enriched, and reported on. Finally, both incoming and outgoing flows to the AWS platform input data for complex AI questionnaires.

Not only did we face difficulties in integration, but data modeling also brought challenges. One of the biggest hurdles we had to overcome was performance. As SAP Datasphere offers several possibilities to persist and replicate data, we had to find out what works best in which situation. Currently, we use task chains when there is data dependency, we persist data after transformation for complex data models, and make use data snapshots for faster response in the reports.

This section zooms in on the reporting and analytics solutions the team brought for the Versuni Operations Vertical. Operations, or order-to-cash, entails the process from planning receiving a customer order, to receiving payments for the goods or services delivered, and everything in between; manufacturing, procurement, supply chain and quality & regulatory. Reporting in the operations area within SAP plays a crucial role in providing insights into the performance and efficiency of the entire order-to-cash cycle. Therefore, it was important for us to understand what the business needed in order to be able to effectively measure this. By utilizing our functional SAP knowledge, we challenged and translated these requirements into sustainable data models and eventually clear, easy-to-use reports or Dashboards.

Within the supply chain domain, we have created several reports related to integrated warehousing and distribution. These reports had to capture the incoming and outgoing goods flow and its related costs. One of the reports related to the outgoing goods flow, gives a holistic view on the outbound delivery process, allowing users to quickly monitor the outbound goods flow and act on exceptions, but also to check upon completeness across the different parties. Another example is a report that gives an overview of the costs made per delivery during the whole delivery process, allowing users to search for opportunities to decrease costs, but also to check whether cost-cutting activities are effective. Lastly, related to the flow of incoming goods, there is a report that indicates whether a container is within the transport process. This allows the warehousing partner to plan and process the incoming containers.

A second topic within the supply chain domain is OTIF (On-Time-In-Full). OTIF is a metric used by the customer excellence team to measure the percentage of customer orders that are delivered on time and in the correct quantity. Failing to meet OTIF targets can have several negative impacts on customers and sales, including dissatisfied customers, lost sales, damage to reputation, and increased costs. By improving OTIF performance, the business can improve customer satisfaction, increase sales, and protect their reputation. To improve performance and allow for informed decision-making, we had to introduce reliable, comprehensive sets of data coupled with reports and dashboards that supported this process.

For OTIF we made it possible to perform Root Cause analyses on several topics. One of the Root Cause analyses can be done on availability where it is possible to see why something was either not on-time, not in-full or neither. Some probable causes include: an allocation or process error, the absence of a material plan in IBP or insufficient stock on hand due to back orders.

In the quality & regulatory domain, an important report is the Field Call Rate (FCR) report. FCR is a quality metric that very roughly indicates the number of product returns as a percentage of product sales volume. Thereby giving insights into what should be reserved for warranty-related questions from customers around the world. The FCR of a product is the number of accepted warranty claims as a percentage of sales volume that are still in the warranty period (Sales packet). The FCR covers a prediction for a 24-month warranty period.

There are, however, a few challenging differences between theory and reality:

• Since most of Versuni’s products are not directly sold to consumers, but to distributors, we do not know how many products were sold to consumers in an area. For FCR, we introduced the pipeline parameter for this. This parameter is the number of months of delay between the sales we see in the system and the assumed actual sales. This parameter is usually 2 or 3.

• FCR is intended to be used for prediction, but it only uses fitted parameters from historical data. This limits its use: it only looks back and adjusts after the fact.

For procurement, a spend & savings report has been created. It is used by the business to measure spending costs, increase process efficiency, or improve supplier relationships. It gives a comprehensive view of the metrics that drive improved cost savings and supply-chain performance. Having visibility on spending allows us to meet cost-reduction goals and follow up on incremental savings initiatives. Improved visibility helps identify cost-saving opportunities by reducing wasteful and maverick spending. The spend and savings report helps stakeholders to benchmark vendors and their contract terms. Knowing this can help focus efforts on getting the best value from these preferred vendors and consolidating the relationships.

A successful SAP Datasphere Cloud implementation is not just a technological upgrade. It is a strategic move towards a more efficient and responsive warehouse management system. In an era where data is one of the most important parts of business, organizations are presented with a unique opportunity to not only manage their data effectively but also to derive actionable insights that propel them forward in the competitive landscape. Complementing this orchestration, SAP Analytics Cloud emerges as a powerful tool for visualization, analysis, and informed decision-making. Its user-friendly interface empowers stakeholders across the organization to interact with data in meaningful ways, transforming raw information into actionable insights that drive innovation and efficiency.

While this all sounds great, in the end a successful implementation all succeeds or fails through bringing business value to the enterprise by challenging business requirements. For that, you need to have an implementation partner with the right technical expertise, not just with tools in the BI landscape, but also with functional SAP and business knowledge. Furthermore, that partner needs to be able to translate the business requirements into actionable and valuable building blocks for your data architecture. If you're looking for support in converting your data into meaningful insights and unlocking business value, we've got the perfect partner for you.